Chargeback Prevention Policy Playbook: A Fill-In Template for Shopify Merchants

Prevention fails at the policy layer, not the dispute layer

Most chargeback problems trace back to the same root: no written policy. Fraud screening lives in someone's head. Escalation depends on who's working that day. Customer communication is improvised per order. When a dispute lands in Shopify Admin under Orders → [Order] → Dispute, it's already too late to fix the upstream decisions that created it.

This playbook gives you a documented, repeatable prevention structure. Fill in the brackets, assign the owners, and run it consistently. The goal isn't zero chargebacks — it's eliminating the preventable ones.

When to use this playbook

Deploy this when you're setting up prevention for the first time, after a chargeback rate spike, after a fraud event that exposed a gap, or when onboarding a new ops team member who needs documented rules instead of tribal knowledge. If your chargeback rate is above 0.65% (Visa's monitoring threshold — confirm current thresholds with your acquirer), treat this as urgent, not optional.

Step-by-step: building your prevention policy

Step 1 — Define your fraud screening rules

Write down exactly which signals trigger a hold, a manual review, or an automatic cancel. If it's not written, it won't be applied consistently. At minimum, document your thresholds for: order value, AVS/CVV mismatch behavior, IP-to-billing address distance, velocity (same card, multiple orders), and freight-forwarder or reshipper address patterns.

Shopify's fraud analysis score (visible under Orders → [Order] → Fraud analysis) surfaces several of these signals automatically. Your policy needs to define what score range triggers what action — not leave it to individual judgment.

Step 2 — Map your customer communication triggers

Chargebacks labeled "Item Not Received" are frequently preventable with proactive communication. Write down exactly when customers receive shipping confirmation, delay notifications, and delivery confirmation. Silence between order and delivery is where INR disputes incubate.

Step 3 — Document your escalation path

Who reviews a flagged order? Who approves a cancel on a high-value hold? Who owns the dispute response if the original order handler is unavailable? Every gap in this chain is a future loss.

Step 4 — Set your refund-before-dispute threshold

Some disputes are cheaper to preempt. Document the order value and evidence-strength combination below which you issue a proactive refund rather than fight. This decision should be policy, not case-by-case instinct.

Step 5 — Review and update cadence

A prevention policy that isn't reviewed is a policy that drifts. Set a calendar trigger — quarterly at minimum — to check whether your fraud rules still match your actual dispute patterns.

Prevention policy template

Customer communication template — delay notification

This is the message most merchants skip. It's also the one that most directly prevents INR disputes.

Subject: Update on your [STORE NAME] order #[ORDER NUMBER]

Hi [CUSTOMER FIRST NAME],

Your order for [PRODUCT NAME OR DESCRIPTION] is taking a little longer than expected to ship. We're currently estimating fulfillment by [REVISED SHIP DATE].

If you have questions or want to make changes, reply to this email or reach us at [SUPPORT EMAIL OR PHONE]. We'll keep you updated as soon as your order ships.

— [STORE NAME] Support

Filled example — electronics merchant, $380 order

Where this policy breaks down in practice

A merchant running a $380 electronics order through manual review flagged it correctly — IP in a different state, Medium fraud score in Shopify's fraud analysis panel, billing address matched a known reshipper ZIP. The reviewer approved it anyway because the customer had called in and sounded credible. No written rule covered "customer called in." The order shipped. The chargeback came 22 days later.

The failure wasn't the fraud screening rule. It was the absence of a rule covering override conditions. If your policy doesn't specify when a human can override a flag — and what approval that requires — the policy has a hole. Document override conditions explicitly, or they become the default exception.

A second common failure: the policy exists but only one person knows where it lives. When that person is out, decisions revert to instinct. Store the policy somewhere the whole ops team can access — not in a personal folder or a Slack DM thread.